This invention relates generally to social networking, and more specifically to classify content items and thereby distinguish content items of different qualities.
Social networking systems allow users to connect and interact with each other. Users of social networking systems are typically interested in learning about actions performed by other users that are connected to the user in a social networking system. These actions may include photo uploads, status updates, transactions, wall or timeline posts, postings of comments, recommendations, likes indicated on content published by other users. Businesses, brands, groups, public figures, etc., can also post content on their pages. The posted content can then be provided to users following those pages. A user may be connected to many other users in a social networking system and a large number of stories reflecting actions taken by those other users or stories/posts from pages may be generated on a regular basis, any of which can be provided to the user on the social networking system in, for example, a newsfeed.
A user may have a preference for certain types stories compared to others, and there are certain stories that include higher-quality content than others. Presenting to each user stories that are more appealing to that user and are of higher-quality provides value to the social networking system in that it increases the chances of retaining the user, and encourages the user to be more engaged with the social networking system, and this in turn creates more business opportunities, such as advertising opportunities.
Nevertheless, it can be challenging to distinguish stores that are of value to a user from lower-quality stories, and to ensure that the user's newsfeed of stories continues over time to contain mostly high-quality stories. Lower-quality stories (e.g., spam content, meme content, and other junk-type content) are often specifically designed to encourage engagement by users. Thus, simply considering which stories have the highest engagement rate for the user and for other users may not be a sufficient way to determine what types of stories are actually the highest-quality stories for the user. Relying solely on past engagement rates may result in the user's newsfeed eventually being overrun by these lower-quality stories.
To encourage users' engagement in a social networking system, the user should be presented with high-quality stories that are of interest to the user. Each time there is an opportunity to present stories to a user, the social networking system will typically have a large collection of stories to choose from for that user. To select the best, highest-quality stories and to order them within the newsfeed, the social networking system uses a ranking algorithm to rank all of these story options for the user. Ranking that is primarily based on a user's past engagement with stories or predicted future engagement may promote low-quality content that a user does not wish to view since such low-quality content is often designed to increase its visibility in social networking systems. This low quality content may be disproportionately selected for inclusion in newsfeeds because of its high engagement rate among users, eventually resulting in this low quality content filling a majority of users' newsfeeds, which may frustrate users and cause users to be less engaged in social networking systems.